A complete guide to K-means clustering algorithm

Everything you need to know about a top algorithm in Machine Learning

Introduction:

When dealing with building machine learning models, Data scientists spend most of the time on 2 main tasks when building machine learning models

Pre-processing and Cleaning

The major portion of time goes in to collecting, understanding, and analysing, cleaning the data and then building features. All the above steps mentioned are very important and critical to build successful machine learning…

Price errors and their impact:



Price errors are one of the ways in which revenue leakage occurs in e-commerce business. Although retailers put various checks and balances in place, pricing errors are still common. Data entry mistakes, misplaced decimal points, reversal of digits, and other clerical errors made in hurry are the major contributors. It can also occur because errors in feeding promotional offer dates. Promotions might unintendedly start early or end late. Such revenue…

What is Automated Machine Learning? Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals.

With the right tools, today’s average business user can become a Citizen Data Scientist, using data integrated from various sources to learn, test theories and make decisions. AutoML comes into play as…

Summary: The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out and once again there are big changes in the leaderboard.  Some major incumbents have fallen and some new challengers have emerged.

The Gartner Magic Quadrant for Data Science and Machine Learning Platforms is just out and once again there are big changes in the leaderboard.  Say what you will about our profession but as a platform developer you…

October is historically the most volatile month for stocks, but is this a persistent signal or just noise in the data?

Stocks, Significance Testing & p-Hacking. Follow me on Twitter (twitter.com/pdquant) for more. Over the past 32 years, October has been the most volatile month on average for the S&P500 and December the least, in this article we will use simulation to assess the…

How machines process and understand human language

Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our tone, our selection of words, everything adds some type of information that can be interpreted and value extracted from it. In theory, we can understand and even predict human behaviour using that information.…

Machine learning is the branch of computer science and a subfield of Artificial Intelligence that utilizes past data to learn from and use its knowledge to make future decisions. Machine learning is at the intersection of computer science, engineering, and statistics. The goal of machine learning is to generalize a detectable pattern or to create an unknown rule from given examples.



Machine learning is broadly classified into three categories but nonetheless, based on the…

An important principle of data science is that data mining is a process. It includes the application of information technology, such as the automated discovery and evaluation of patterns from data. It also includes an analyst’s creativity, business knowledge, and common sense. Understanding the whole process helps to structure data mining projects.

Since the data mining process breaks up the overall task…

                                                                                                  Source: www.mstecker.com/…

Artificial Intelligence and Machine Learning are two terms related to the world of computer science that can be heard a lot these days. These technologies are helping to bring about a considerable change in different fields today. Be it medical sciences, meteorology, robotics, understanding customer perspectives or scientific developments; these fields are offering an excellent way to move forward without letting technology stagnate.…

Introduction: Deriving meaningful information out of heap of data is the minimal requirement for any establishment today for its survival & sustenance. There are many terminologies and buzz words related to this area that blurs the meaning leaving people confused, such as Bigdata, Data Ware house (DWH), BI analytics, AI (Artificial…

Lee Sedol Vs Alpha Go

When I worked as a McKinsey consultant, I served the CEO of a bank regarding his small business strategy. I wanted to run regressions on the bank's data but I was advised against it: "They don't even understand statistics. How are you going to explain a regression to…

For any business, the worst scenario is getting out of product inventory when customers are ready to buy your product. Keeping a stock of every item in the store is another burden to carry for every business. This trade off has been even more problematic in current times, when manufacturing firms are flooding with SKUs (Stock Keeping Unit) ranging from product sizes, flavours, styles etc. To cater personalised demand companies are customising…

What is NLP?

Natural Language Processing (NLP) can be simply defined as teaching an algorithm to read and analyze human (natural) languages just like the human brain does, but a lot faster than a human could, more accurately and on very large amounts of data.

It is a great skill to have if you are an aspiring data scientist or data analyst because has…

I built a scenario for a hybrid machine learning infrastructure leveraging Apache Kafka as scalable central nervous system. The public cloud is used for training analytic models at extreme scale (e.g. using TensorFlow and TPUs on Google Cloud Platform (GCP) via Google ML Engine. The predictions (i.e.…

These are a bulk of people pondering the same question and exploring different answers but at a hanging stage not knowing which one is correct and which one should they follow. The answers are very conflicting some share it on the basis of the research while some share their personal experience which confuses the newbies as hell. Well, the answer to this question depends on what you are trying to…